class_docstr: The class for binary operations of pandas-on-Spark objects with spark type:
  TimestampNTZType.
code: def astype(
      self, index_ops: IndexOpsLike, dtype: Union[str, type, Dtype]
  ) -> IndexOpsLike:
      dtype, spark_type = pandas_on_spark_type(dtype)
  
      if isinstance(dtype, CategoricalDtype):
          return _as_categorical_type(index_ops, dtype, spark_type)
      elif isinstance(spark_type, NumericType):
          from pyspark.pandas.internal import InternalField
  
          scol = self._cast_spark_column_timestamp_to_long(
              index_ops.spark.column
          ).cast(spark_type)
          return index_ops._with_new_scol(
              scol, field=InternalField(dtype=dtype)
          )
      else:
          return super(DatetimeNTZOps, self).astype(index_ops, dtype)
  
imports: import datetime
  import warnings
  from typing import Any, Union, cast
  import numpy
  import pandas
  from pandas.api.types import CategoricalDtype
  from pyspark import SparkContext
  from pyspark.sql import Column, functions
  from pyspark.sql.types import BooleanType, LongType, StringType, TimestampType, TimestampNTZType, NumericType
  from pyspark.sql.utils import pyspark_column_op
  from pyspark.pandas._typing import Dtype, IndexOpsLike, SeriesOrIndex
  from pyspark.pandas.base import IndexOpsMixin
  from pyspark.pandas.data_type_ops.base import DataTypeOps, _as_categorical_type, _as_other_type, _as_string_type, _sanitize_list_like
  from pyspark.pandas.typedef import pandas_on_spark_type
label_desc: Use image node_id 2 for calling the DatetimeNTZOps obj's underlying member method code with example usage: obj.astype(index_ops, dtype) and returns: _as_categorical_type, index_ops, super